面向自动驾驶的世界模型：初步综述
World Models for Autonomous Driving: An Initial Survey
AI总结：
本文初步综述了世界模型在自动驾驶中的理论基础、实际应用与研究进展，强调其通过综合传感器数据预测未来场景、弥补信息缺口以辅助决策，并旨在为该领域提供基础参考。
摘要：
在快速演进的自动驾驶领域中，准确预测未来事件并评估其影响的能力对于安全性和效率至关重要，能够关键性地辅助决策过程。世界模型已成为一种变革性方法，使自动驾驶系统能够综合并解读大量传感器数据，从而预测潜在的未来场景并弥补信息缺口。本文对世界模型在自动驾驶中的现状与前瞻性进展进行了初步综述，涵盖其理论基础、实际应用以及旨在克服现有局限性的持续研究工作。本综述强调了世界模型在推动自动驾驶技术发展中的重要作用，旨在为研究界提供一份基础性参考，便于快速了解和把握这一新兴领域，并激发持续的创新与探索。
英文摘要：
In the rapidly evolving landscape of autonomous driving, the capability to accurately predict future events and assess their implications is paramount for both safety and efficiency, critically aiding the decision-making process. World models have emerged as a transformative approach, enabling autonomous driving systems to synthesize and interpret vast amounts of sensor data, thereby predicting potential future scenarios and compensating for information gaps. This paper provides an initial review of the current state and prospective advancements of world models in autonomous driving, spanning their theoretical underpinnings, practical applications, and the ongoing research efforts aimed at overcoming existing limitations. Highlighting the significant role of world models in advancing autonomous driving technologies, this survey aspires to serve as a foundational reference for the research community, facilitating swift access to and comprehension of this burgeoning field, and inspiring continued innovation and exploration.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
